code: def __init__(self):
      super().__init__(
          algorithm=ACERAlgorithmParameters(),
          exploration={DiscreteActionSpace: CategoricalParameters()},
          memory=EpisodicExperienceReplayParameters(),
          networks={"main": ACERNetworkParameters()},
      )
  
imports: from typing import Union
  import numpy
  from rl_coach.agents.policy_optimization_agent import PolicyOptimizationAgent
  from rl_coach.architectures.embedder_parameters import InputEmbedderParameters
  from rl_coach.architectures.head_parameters import ACERPolicyHeadParameters, QHeadParameters
  from rl_coach.architectures.middleware_parameters import FCMiddlewareParameters
  from rl_coach.base_parameters import AlgorithmParameters, NetworkParameters, AgentParameters
  from rl_coach.core_types import Batch
  from rl_coach.exploration_policies.categorical import CategoricalParameters
  from rl_coach.memories.episodic.episodic_experience_replay import EpisodicExperienceReplayParameters
  from rl_coach.spaces import DiscreteActionSpace
  from rl_coach.utils import eps, last_sample
label_desc: Use image node_id 1 to create a new ACERAgentParameters object from inherited base classes: AgentParameters with example: obj = ACERAgentParameters()